Jobs / United States / Target Corporation
Lead Machine Learning Engineer - Merchandising AI (ML Ops)
Target Corporation · 🇺🇸 7000 Target Pkwy N,NCD-0375 Brooklyn Park,MN 55445
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 107 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Target Corporation paid sponsored hires in similar roles46 certified filings for “Lead Engineer” (Software Developers) in MN: $135k–$145k, median $145k. Most were filed at wage level IV (83%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Target Corporation
The US Department of Labor certified 107 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Target Corporation →
About the role
The pay range is $132,000.00 - $238,000.00 Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits . JOIN US AS A LEAD MACHINE LEARNING ENGINEER – MERCHANDISING AI About Us: Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here . A role with Target Data Sciences means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Applied Data Sciences or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Digital Marketing, Supply Chain Optimization, Advanced AI, Search and Personalization rely on. Every Scientist on Target’s Data Sciences team can expect modeling and data science, software/product development of highly performant code for model performance at scale. As the Lead Machine Learning Engineer – Merchandising, you will join a Data Sciences team responsible for creating and optimizing the data and models used to build a world-class merchandising product. You will play a crucial role in designing, implementing, and optimizing production machine learning solutions. We will also expect you to understand best practice software design, participate in code reviews, and create a maintainable well-tested codebase with relevant documentation. At an organizational level, you may conduct training sessions, present work to technical and non-technical peers/leaders, build knowledge on business priorities/strategic goals and leverage this knowledge while building requirements and solutions for each business need. Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs. About you: • 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience • MS in Computer Science, Applied Mathematics, Statistics, Physics or equivalent work or industry experience in applied machine learning • 5 plus years of experience in end-to-end machine learning application development, including data pipelining, model optimization, deployment and API design • Extensive experience with applied machine learning frameworks and the ability to developing highly distributed machine learning systems at scale • Highly proficient in Python programming • Strong understanding of CI/CD practices for machine learning systems and ML Ops principles • Extensive experience with Google Cloud’s Vertex AI and/or the broader cloud-based ML ecosystem • Demonstrated knowledge of various testing frameworks and containerization like Docker and Kubernetes • Lead the development of agentic AI solutions that connect data, tools, APIs and business rules into end-to-end decisioning workflows • Demonstrated experience in REST API design and development •